AI Development Consultant
Who Actually Builds the AI

Reliability

The system behaves predictably enough to trust

The point is not a flashy demo. It is an AI feature that behaves consistently under imperfect inputs and real user pressure.

Economics

The cost model makes business sense

Model usage, caching, workflow design, and tooling choices should support the startup’s economics instead of quietly undermining them.

Advantage

AI becomes part of the product, not just a wrapper

The strongest implementations improve the actual workflow and user value, rather than adding superficial “AI” branding.

Autonomous AI Agents

Agents that reason, plan, and execute tasks — with proper error handling, retry logic, and monitoring. Not demos.

RAG Pipelines

Connect LLMs to your actual data. Accurate, up-to-date responses grounded in your knowledge base.

LLM Integration

OpenAI, Claude, Gemini — integrated into your product with proper abstraction layers for flexibility.

AI Feature Development

AI-powered search, recommendations, summarization, classification — built into your product, not bolted on.

AI Workflow Automation

Automate document processing, data extraction, and QA — things that used to need humans, now handled by AI.

AI Observability

Monitor outputs, track costs, detect drift. You know when your AI misbehaves before users complain.

AI that ships vs. AI demos

Most AI projects fail because they look impressive in presentations but fall apart in production. I build AI that users depend on — not prototypes that break under real usage.

Cost control from day one

LLM costs spiral without architecture. I implement caching, batching, and smart model selection so your AI costs stay predictable.

I build AND advise

I can consult on AI strategy, or I can build the AI system myself. Most clients want both — strategic guidance with someone who can execute.

Production-grade, not prototype-grade

Guardrails, error handling, fallbacks, monitoring. Your AI does not crash your product when it encounters an edge case.

Direct access to the builder

No AI consultants who resell OpenAI APIs. You work directly with someone who has built autonomous agents in production.

US time zone, fast turnaround

I work with SF, NY, and Austin founders daily. Slack, async updates, scheduled calls — whatever keeps your startup moving.

Which AI models do you actually choose for US startup products?

All of them — OpenAI, Anthropic Claude, Google Gemini, open-source models. I pick the right model for the task, budget, and latency requirements.

How do you stop AI features from creating expensive product mistakes?

I implement validation layers, cost caps, human-in-the-loop checkpoints for high-stakes decisions, and real-time monitoring. AI failures do not become product failures.

Can you add AI to an existing SaaS or internal workflow without rebuilding it?

Yes. Most of my AI work is adding AI capabilities to existing products. I integrate cleanly with your stack — no ripping and replacing.

What does AI development usually cost for a startup use case?

Simple LLM integrations start at a few thousand. Autonomous agents with RAG can run higher. I give fixed-price quotes after scoping.

How do you handle AI compliance, privacy, and regulated data concerns?

I implement proper data handling for GDPR and similar regulations. I also assess whether your AI use case triggers specific compliance requirements.

Are you available during US founder and product-team hours?

Yes. I work with Pacific to Eastern time zones. Most of my AI clients are in SF and NY.